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Model Integration in Computational Biology: The Role of Reproducibility, Credibility and Utility.

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Mathematical modeling is crucial for pandemic response. A reproducibility crisis hinders reusing and integrating these vital disease transmission models, impacting future public health preparedness.

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Area of Science:

  • * Mathematical modeling
  • * Epidemiology
  • * Public health

Background:

  • * Mathematical modeling of disease transmission became essential during the COVID-19 pandemic for informing critical state decisions.
  • * Advancements in host-viral modeling are needed to prepare for future pandemics.
  • * A significant reproducibility crisis was identified, impeding the reuse and integration of existing models.

Purpose of the Study:

  • * To summarize discussions among scientists on host-viral modeling for future pandemics.
  • * To identify challenges hindering model utility and integration.
  • * To present existing efforts and propose future solutions for enhanced model integration.

Main Methods:

  • * Synthesis of expert discussions on mathematical modeling challenges.
  • * Analysis of the reproducibility crisis in epidemiological modeling.
  • * Review of current initiatives addressing model integration and utility.

Main Results:

  • * Identified a critical reproducibility crisis in disease transmission modeling.
  • * Highlighted the inability to reuse and integrate models due to this crisis.
  • * Documented existing efforts and challenges toward future solutions.

Conclusions:

  • * Addressing the reproducibility crisis is essential for advancing multi-scale modeling.
  • * Failure to resolve these issues will limit the scientific community's ability to build and implement impactful models for health crises.
  • * Enhanced model utility and integration are necessary for future pandemic preparedness.